Radiomics, machine learning, and artificial intelligence-what the neuroradiologist needs to know.

Abstract

Authors

• Matthias W Wagner
  Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Raemistrasse 100, 8091, Zurich, Switzerland.
• Khashayar Namdar
  Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada.
• Asthik Biswas
  Division of Neuroradiology, The Hospital for Sick Children, Toronto, Canada.
• Suranna Monah
  Division of Neuroradiology, The Hospital for Sick Children, Toronto, Canada.
• Farzad Khalvati
  Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada. farzad.khalvati@utoronto.ca.
• Birgit B Ertl-Wagner
  From the Department of Radiology, University of Wisconsin Madison School of Medicine and Public Health, 600 Highland Dr, Madison, WI 53792 (D.A.B., M.L.S.); Department of Radiology, New York University, New York, NY (L.M.); Department of Musculoskeletal Radiology (M.A.B.) and Institute for Technology Assessment (E.F.H.), Massachusetts General Hospital, Boston, Mass; Department of Medical Imaging, Hospital for Sick Children, University of Toronto, Toronto, Canada (B.B.E.W.); Department of Radiology, University of California-San Diego, San Diego, Calif (K.J.F.); Department of Cancer Imaging, Division of Imaging Sciences & Biomedical Engineering, Kings College London, London, England (V.J.G.); Department of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, Calif (C.P.H.); and Department of Radiology and Radiologic Science, The Johns Hopkins University School of Medicine, Baltimore, Md (C.R.W.).

Keywords

External Resources